Data Entry in SPSS, Regression, Multivariate analysis, Classification of Qualitative Data with SPSS, Principal Component Analysis, Probability Distributions, Sample Descriptive Measures ...

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...

SPSS is the name of a series of software packages used for data analysis. Its main selling point is that it allows scientific researchers, teachers and students to quickly analyze data without ...

Compositional data, consisting of vectors of proportions, have proved difficult to handle statistically because of the awkward constraint that the components of each vector must sum to unity. Moreover ...

Principal component analysis is often incorporated into genome-wide expression studies, but what is it and how can it be used to explore high-dimensional data?

However, PCA suffers from the fact that each principal component is a linear combination of all the original variables, thus it is often difficult to interpret the results. We introduce a new method ...